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Real-Time Tracking of Time-Varying Cable Frequency Based on a Time-Domain Signal Processing Method

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  • Zhongqi Shi

    (Key Laboratory of Urban Safety Risk Monitoring and Early Warning, Ministry of Emergency Management, Shenzhen 518055, China
    Shenzhen Technology Institute of Urban Public Safety, Shenzhen 518000, China
    National Science and Technology Institute of Urban Safety Development, Shenzhen 518000, China)

  • Rumian Zhong

    (Key Laboratory of Urban Safety Risk Monitoring and Early Warning, Ministry of Emergency Management, Shenzhen 518055, China
    Shenzhen Technology Institute of Urban Public Safety, Shenzhen 518000, China
    National Science and Technology Institute of Urban Safety Development, Shenzhen 518000, China)

  • Nan Jin

    (Key Laboratory of Urban Safety Risk Monitoring and Early Warning, Ministry of Emergency Management, Shenzhen 518055, China
    Shenzhen Technology Institute of Urban Public Safety, Shenzhen 518000, China
    National Science and Technology Institute of Urban Safety Development, Shenzhen 518000, China)

Abstract

In this paper, a time-domain signal processing method is proposed to extract the real-time time-varying cable frequency. The proposed conjugate-pair decomposition (CPD) method uses empirical mode decomposition (EMD) to obtain intrinsic mode functions (IMFs), and then the instantaneous frequency can be extracted by post-processing the conjugate-pair of IMFs. Several numerical simulations and a composite cable-stayed bridge experiment are used to validate the accuracy and capability of the proposed method for tracking time-varying cable frequency. Moreover, the proposed method may be further used to assess cable fatigue damage.

Suggested Citation

  • Zhongqi Shi & Rumian Zhong & Nan Jin, 2023. "Real-Time Tracking of Time-Varying Cable Frequency Based on a Time-Domain Signal Processing Method," Sustainability, MDPI, vol. 15(2), pages 1-12, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1700-:d:1037321
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    References listed on IDEAS

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    1. Norden E. Huang & Man‐Li Wu & Wendong Qu & Steven R. Long & Samuel S. P. Shen, 2003. "Applications of Hilbert–Huang transform to non‐stationary financial time series analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 19(3), pages 245-268, July.
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